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Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA

机译:使用关系数据库管理系统对RNA进行基础相互作用预测的协变进化事件分析

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With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.
机译:随着越来越多的序列正确比对,比较序列分析不仅可以准确识别由标准碱基配对形成的常见结构,而且可以准确识别新型结构元素和约束。但是,传统方法的计算量太大,无法在大规模比对中很好地执行,并且对于来自多种系统发育分类的序列而言,效果不佳。我们提出了一种新的方法,该方法利用比对序列的生物的系统发育和进化关系,利用核苷酸位置对之间的协同进化速率。通过一种新颖的数据模式来管理关系数据库中的相关信息,我们的方法(使用Microsoft SQL Server 2005实现)在识别细菌的16S核糖体RNA序列之间的碱基对相互作用方面显示出90%的灵敏度,其规模是40倍大,而50倍比以前的研究提高了%的灵敏度。结果还表明,二级结构螺旋中的几套交叉链碱基堆叠对的协变信号以及RNA结构中的其他细微约束。

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